Spinal cord multi‐parametric magnetic resonance imaging for survival prediction in amyotrophic lateral sclerosis

• Published in: European journal of neurology Vol. 24; no. 8; pp. 1040 - 1046
• Main Authors: Querin, G., El Mendili, M. M., Lenglet, T., Delphine, S., Marchand‐Pauvert, V., Benali, H., Pradat, P.‐F.
• Format: Journal Article
• Language: English
• Published: England John Wiley & Sons, Inc 01.08.2017; Wiley
• Subjects: Adult; Aged; Amyotrophic lateral sclerosis; Amyotrophic Lateral Sclerosis - diagnostic imaging; Amyotrophic Lateral Sclerosis - mortality; Amyotrophic Lateral Sclerosis - pathology; Anisotropy; Atrophy; Bioengineering; Biomarkers; Cross-Sectional Studies; Diffusion Tensor Imaging - methods; Disease Progression; Female; Humans; Imaging; Life Sciences; Magnetic resonance imaging; Magnetic Resonance Imaging - methods; Male; Mathematical models; Medical imaging; Middle Aged; motor neuron degeneration; Multimodal Imaging; Neuroimaging; Neurology; Neurons and Cognition; NMR; Nuclear magnetic resonance; Patients; Predictions; Prognosis; Resonance; Spinal cord; Spinal Cord - diagnostic imaging; Spinal Cord - pathology; spinal cord atrophy; spinal cord MRI; Survival; survival prediction; Survival Rate; Vertebrae; spinal cord MRI; spinal cord atrophy; survival prediction; motor neuron degeneration; amyotrophic lateral sclerosis; biomarkers
• DOI: 10.1111/ene.13329
• ISSN: 1351-5101

Background and purpose Assessing survival is a critical issue in patients with amyotrophic lateral sclerosis (ALS). Neuroimaging seems to be promising in the assessment of disease severity and several studies also suggest a strong relationship between spinal cord (SC) atrophy described by magnetic resonance imaging (MRI) and disease progression. The aim of the study was to determine the predictive added value of multimodal SC MRI on survival. Methods Forty‐nine ALS patients were recruited and clinical data were collected. Patients were scored on the Revised ALS Functional Rating Scale and manual muscle testing. They were followed longitudinally to assess survival. The cervical SC was imaged using the 3 T MRI system. Cord volume and cross‐sectional area (CSA) at each vertebral level were computed. Diffusion tensor imaging metrics were measured. Imaging metrics and clinical variables were used as inputs for a multivariate Cox regression survival model. Results On building a multivariate Cox regression model with clinical and MRI parameters, fractional anisotropy, magnetization transfer ratio and CSA at C2–C3, C4–C5, C5–C6 and C6–C7 vertebral levels were significant. Moreover, the hazard ratio calculated for CSA at the C3–C4 and C5–C6 levels indicated an increased risk for patients with SC atrophy (respectively 0.66 and 0.68). In our cohort, MRI parameters seem to be more predictive than clinical variables, which had a hazard ratio very close to 1. Conclusions It is suggested that multimodal SC MRI could be a useful tool in survival prediction especially if used at the beginning of the disease and when combined with clinical variables. To validate it as a biomarker, confirmation of the results in bigger independent cohorts of patients is warranted.